Anthropic and OpenAI Growth Slowing, Pressuring AI Infrastructure Investment Chain
nashnova research
Anthropic and OpenAI are both seeing monthly revenue growth decelerate — token volumes keep rising but per-token prices keep falling, shaking the valuation foundations of the entire AI infrastructure chain.
What is happening to revenue at the two leading labs?
Anthropic recently disclosed pre-IPO revenue figures; estimates suggest it will struggle to hit its publicly stated revenue targets, with monthly growth visibly slowing.
OpenAI was flagged last week for a roughly $20 billion revenue shortfall — partly attributed to accounting-basis differences, but enough to force investors to reassess its forward outlook.
This means → the two most closely watched companies in AI are flashing the same warning at the same time: the growth narrative is harder to sustain.
Why does selling more lead to earning less?
The core tension: token usage keeps climbing, but the price per token keeps dropping. Token — the unit AI models use to measure how much text they process.
Models are converging in capability. Google, Meta, Elon Musk's xAI, and Chinese open-source models have all entered the race, collectively crushing pricing power.
In plain terms = think of the ride-hailing wars: more riders every quarter, but too many platforms subsidizing fares — each trip earns less and less.
What does this mean for the AI supply chain?
Anthropic and OpenAI are the anchor tenants of most AI data centers today; the scale of their compute demand sets the capex logic for the entire chain.
If top-lab revenue growth materially slows, valuations face pressure across the board — from emerging cloud providers and hyperscale data-center operators to chip suppliers and the private-credit firms financing expansion.
This means → the market's prior pricing assumption was "AI demand only goes up." Now a harder question surfaces: demand is there, but the ability to pay for it is not keeping pace.
What will DeepSeek's latest move trigger?
DeepSeek released a major model update over the weekend, intensifying the open-source competitive push.
This reflects a structural dynamic: open-source models are systematically lowering the pricing ceiling for commercial models — the more free or cheap alternatives exist, the harder it is for paid models to raise prices.
Expect more near-term volatility in AI stocks as investors watch how leading companies adjust their pricing strategies.
市场有风险，内容仅供研究参考，不构成投资建议。